Progress announced the early-access release of Progress® MarkLogic® Server 12.
DevOps brings enormous competitive advantage to businesses – a fact that's backed up by independent research. For example, the 2018 Accelerate State of DevOps report found that top-performing elite organizations were able to deploy code 46 times more frequently than low performers, had lowered lead times from committing to deploying changes of less than one hour (compared to 1-6 months in low performers), and recovered from incidents 2,604 times faster.
However, at the same time there is an intense and growing focus on data security and privacy. Whether it's through regulations such as the GDPR or increasing consumer expectations that their personal information will be kept safe and used responsibly, it's business-critical that organizations take these concerns seriously.
This is a particular issue when it comes to database DevOps where you also have two different cultures. Database Administrators (DBAs) have traditionally focused on ensuring stability and the security of mission-critical data and information, while developers are looking to quickly create and launch new features to drive competitive advantage.
How can you balance these potentially conflicting demands, yet achieve greater speed through DevOps and still protect the data? While creating a collaborative culture is important, so is technology. Essentially, changing the development process is vital, focusing on four key areas:
1. Standardize
DBAs and developers can both agree that standardizing processes increases speed and ensures consistency. Therefore, look to adopt industry-standard tools for coding, comparison and version control, and roll them out across the wider team so that everyone is using them. At the same time, adhering to naming and design standards along with consistent coding practices will help to streamline the development process.
Tools such as static code analysis software can help by ensuring everyone follows the same standards and known best practices when they develop. This means that whether it's an experienced DBA writing T-SQL code or a less practiced developer, you have a consistent programming structure that can be easily understood, nipping any potential problems in the bud. At the same time, merge code early and often with version control tools to ensure you have a known, shared codebase on which to work.
2. Automate
Particularly when it comes to database deployments, you need a repeatable, reliable and low risk process to ensure trouble-free DevOps implementations. What I call ‘continuous stuff' (continuous integration, continuous delivery and continuous deployment) plays a leading role in achieving this.
Continuous integration gives quick feedback to the development team, while continuous delivery ensures that changes are made quickly, and continuous deployment demonstrates that the organization trusts its teams to deliver DevOps.
Automation dramatically brings down time to market, but (going back to standardization), you need the right tools and processes in place if it's to be truly effective.
3. Monitor
DevOps is a continuous process and as an organization you need to continually improve how you operate. Monitoring operations therefore has two key roles. Clearly, it highlights potentially disruptive operational and performance issues, allowing you to fix them quickly, hopefully before they develop into more serious problems. More importantly, it gives you vital insights that allow you to optimize operations moving forward.
That means you need to add continuous monitoring to your other tools, with DBAs and other operational staff regularly sharing reports with developers to improve performance. We're now living in a feedback-driven society, and development is no different. We all need to know whether we're doing a good job, and how we can get better. It could be something as small as adjusting coding habits, but there's no way that teams will progress if they don't know there's an issue.
4. Protect
As I said at the beginning of this article, there's growing pressure to protect data and ensure the highest levels of security. This should be good practice for every organization – and if you needed any further reason to take it seriously, look at the enormous fines you could be liable for under regulations such as the GDPR.
Yet sharing accurate, real-world data is crucial to successfully developing new code and features. That means adopting tools for data masking and anonymization that can protect confidential and personal information, while still providing data for development and testing that has the same size and shape as the real data in the production database. You also need to be able to audit where data is shared within your organization and ensure it's protected at every point.
Summary
Changing the development process to ensure DevOps flourishes requires a combination of collaboration and technology. Following these four steps is therefore crucial to starting on your DevOps journey, bringing DBAs and developers together through standardization, automation, monitoring and data protection.
Industry News
Red Hat announced the general availability of Red Hat Enterprise Linux (RHEL) AI across the hybrid cloud.
Jitterbit announced its unified AI-infused, low-code Harmony platform.
Akuity announced the launch of KubeVision, a feature within the Akuity Platform.
Couchbase announced Capella Free Tier, a free developer environment designed to empower developers to evaluate and explore products and test new features without time constraints.
Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company, announced the general availability of AWS Parallel Computing Service, a new managed service that helps customers easily set up and manage high performance computing (HPC) clusters so they can run scientific and engineering workloads at virtually any scale on AWS.
Dell Technologies and Red Hat are bringing Red Hat Enterprise Linux AI (RHEL AI), a foundation model platform built on an AI-optimized operating system that enables users to more seamlessly develop, test and deploy artificial intelligence (AI) and generative AI (gen AI) models, to Dell PowerEdge servers.
Couchbase announced that Couchbase Mobile is generally available with vector search, which makes it possible for customers to offer similarity and hybrid search in their applications on mobile and at the edge.
Seekr announced the launch of SeekrFlow as a complete end-to-end AI platform for training, validating, deploying, and scaling trusted enterprise AI applications through an intuitive and simple to use web user interface (UI).
Check Point® Software Technologies Ltd. unveiled its innovative Portal designed for both managed security service providers (MSSPs) and distributors.
Couchbase officially launched Capella™ Columnar on AWS, which helps organizations streamline the development of adaptive applications by enabling real-time data analysis alongside operational workloads within a single database platform.
Mend.io unveiled the Mend AppSec Platform, a solution designed to help businesses transform application security programs into proactive programs that reduce application risk.
Elastic announced that it is adding the GNU Affero General Public License v3 (AGPL) as an option for users to license the free part of the Elasticsearch and Kibana source code that is available under Server Side Public License 1.0 (SSPL 1.0) and Elastic License 2.0 (ELv2).
Progress announced the latest release of Progress® Semaphore™, its metadata management and semantic AI platform.
Elastic, the Search AI Company, announced the Elasticsearch Open Inference API now integrates with Anthropic, providing developers with seamless access to Anthropic’s Claude, including Claude 3.5 Sonnet, Claude 3 Haiku and Claude 3 Opus, directly from their Anthropic account.